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Vieri, M.P
Bouchard, M
Reisinger, S
Shorkey, R
Kumpatla, S
Shahinian, M
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Authors
Reese, C.L
Clay, D.E
Beck, D.L
Clay, S.A
Long, D.S
Shahinian, M
Pagni, P
Ghinassi, G.P
Vieri, M.P
Reisinger, S
Uhlmann, N
Hanke, R
Gerth, S
Kablan, L
Chabot, V
Mailloux, A
Bouchard, M
Fontaine, D
Bruulsema, T
Sridharan, S
Sornapudi, S
Hu, Q
Kumpatla, S
Bier, J
Shorkey, R
Topics
Remote Sensing Applications in Precision Agriculture
Sensor Application in Managing In-season Crop Variability
Sensor Application in Managing In-season CropVariability
Site-Specific Nutrient, Lime and Seed Management
Big Data, Data Mining and Deep Learning
Industry Sponsors
Type
Oral
Poster
Year
2010
2014
2018
2022
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Filter results6 paper(s) found.

1. Optimizing Vineyard Irrigation Through The Automatic Resistivity Profiling (arp) Technology. The Proposal Of A Methodological Approach

 In Tuscany, central Italy, grape cultivation and wine production (i.e., Chianti DOCG, Brunello di Montalcino) are farming activities appreciated worldwide. Differently from the past, irrigation is allowed to meet the intense physiological stress that may occur during seasons affected by the increasing climate variability, in order to guarantee quality product and hence high market profitability in many vines areas. Most vineyards... P. Pagni, G.P. Ghinassi, M.P. Vieri

2. X-Ray Computed Tomography For State Of The Art Plant And Root Analysis

During the last years, the formerly in medical applications established technique of X-ray computed tomography (CT) is used for non-destructive material analysis as well. Adapting this technique for the visualization and analysis of growth processes of plants above and underneath the soil enables new possibilities in the so called smart agriculture. Using State-of-the-art CT systems the computed 3D volume datasets allows the visualization and virtual analysis of hidden structures like roots... S. Reisinger, N. Uhlmann, R. Hanke, S. Gerth

3. Nitrogen And Water Stress Impacts Hard Red Spring Wheat (Triticum Aestivum) Canopy Reflectance

  Remote sensing-based in-season N recommendations have been proposed as a technique to improve N fertilizer use efficiency. Remote sensing estimation of South Dakota hard red spring wheat N requirements needs assessment. Research objectives were: (1) determine the effect of an in-season N application on grain yield, yield loss to nitrogen stress (YLNS), and grain protein; and (2) assess if remote sensing collected at different growth stages may be used to predict yield... C.L. Reese, D.E. Clay, D.L. Beck, S.A. Clay, D.S. Long, M. Shahinian

4. Variability in Corn Yield Response to Nitrogen Fertilizer in Quebec

Optimizing nitrogen (N) fertilization is important to improve corn yield and to reduce N losses to the environment. The economic optimum nitrogen rate  (EONR) is variable and depends on many factors, including weather conditions and crop management.  The main objective of this study was to examine how grain corn yield response to N varies with planting date, soil texture and spring weather across sites and years in Monteregie, which is the most important with 64% of total area and 69%... L. Kablan, V. Chabot, A. Mailloux, M. Bouchard, D. Fontaine, T. Bruulsema

5. A Generative Adversarial Network-based Method for High Fidelity Synthetic Data Augmentation

Digital Agriculture has led to new phenotyping methods that use artificial intelligence and machine learning solutions on image and video data collected from lab, greenhouse, and field environments. The availability of accurately annotated image and video data remains a bottleneck for developing most machine learning and deep learning models. Typically, deep learning models require thousands of unique samples to accurately learn a given task. However, manual annotation of a large dataset will... S. Sridharan, S. Sornapudi, Q. Hu, S. Kumpatla, J. Bier

6. SoilView, LLC

SoilView is an independent provider specializing in precision sampling and field services for agriculture retail, research groups, universities, and the evolving carbon market. Our areas of expertise include sampling for soil nutrients, carbon sampling, soil health and biology, and custom sampling processes for field research. We aim to remove the burden of sample collection for our customers by expertly managing all steps from field collection to final data delivery.   Our... R. Shorkey